Hot water supply apparatus

ABSTRACT

According to one embodiment, a hot water supply apparatus calculates a value representing an ordinary index for the hot water usage of each hot water destination, determines hot water supply whose value is less than a threshold as hot water supply of low ordinary, and determines hot water supply whose value is not less than the threshold as hot water supply of high ordinary. The apparatus also calculates a first boiling-up amount for the hot water supply determined as the hot water supply of low ordinary, and calculates a second boiling-up amount for the hot water supply determined as the hot water supply of high ordinary.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation Application of PCT Application No. PCT/JP2009/065200, filed Aug. 31, 2009, the entire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate generally to a hot water supply apparatus that sets the boiling-up amount in response to a living behavior.

BACKGROUND

A storage hot water supplier boils water in the middle of the night to cover the hot water usage on the next day. If the water is boiled to fill up the tank, the energy used to boil unused water is wasted. There exists a technique for reducing the waste, which collects statistics about the daily hot water usage to determine the boiling-up amount on the next day. In this technique, however, for a day in which the hot water usable is small, the energy for the remaining hot water is wasted.

There exists a technique of performing additional boiling-up when the remaining hot water decreases to an amount below a threshold. In this technique however, hot water in an amount corresponding to the threshold always remains, and the energy required for this is wasted. In addition, use of hot water may start before completion of additional boiling-up, and hot water may run out.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a hot water supply apparatus according to an embodiment;

FIG. 2 is a block diagram showing an example of the hardware configuration;

FIG. 3 is a flowchart illustrating the detailed processing procedure of behavior estimation;

FIG. 4 is a view showing a behavior recording table;

FIG. 5 is a flowchart illustrating the detailed processing procedure of hot water destination determination;

FIG. 6 is a view showing a hot water supply table;

FIG. 7 shows graphs illustrating data of learning target days;

FIG. 8 is a flowchart illustrating the detailed processing procedure of an ordinary index calculation phase;

FIG. 9 is a view showing a hot water supply table representing ordinary indices and ordinary;

FIG. 10 is a flowchart illustrating the detailed processing procedure of midnight boiling-up amount calculation;

FIG. 11 shows graphs illustrating examples of a time-rate change of the hot water supply amount; and

FIG. 12 is a graph showing an example of comparison of the embodiment.

DETAILED DESCRIPTION

In general, according to one embodiment, a hot water supply apparatus calculates a value representing an ordinary index for the hot water usage of each hot water destination, determines hot water supply whose value is less than a threshold as hot water supply of low ordinary, and determines hot water supply whose value is not less than the threshold as hot water supply of high ordinary. The apparatus also calculates a first boiling-up amount for the hot water supply determined as the hot water supply of low ordinary, and calculates a second boiling-up amount for the hot water supply determined as the hot water supply of high ordinary.

As shown in FIG. 1, a hot water supply apparatus according to an embodiment includes a motion sensor 100, a hot water supply amount sensor 200, a hot water supply classification device 300, hot water supply ordinary index calculation devices (to be referred to as “first calculation devices” hereinafter) 400 a to 400 c, a boiling-up amount calculation device (to be referred to as a “second calculation device” hereinafter) 500, and a boiling device 600. There are provided the plurality of first calculation devices 400 a to 400 c corresponding to different hot water destinations.

In this embodiment, three hot water destinations, for example, bath, kitchen, and other hot water supply are defined. That is, the first calculation device 400 a is used for the bath, the first calculation device 400 b is used for the kitchen, and the first calculation device 400 c is used for another hot water supply. These hot water destinations are associated with living environments and, more specifically, living behaviors of persons who use the supplied hot water in the house.

Note that the other hot water supply may be classified more finely in accordance with the living behavior (life pattern). In this case, corresponding first calculation devices are added. This embodiment aims at a hot water supply apparatus (domestic hot water supply apparatus) installed in the human living environment. However, the present embodiment is also applicable to hot water supply apparatuses for other application purposes, for example, a commercial hot water supply apparatus, an industrial water heater, and an industrial superheater.

Referring to FIG. 1, the hot water supply classification device 300 includes a behavior estimation unit 310 and a hot water destination determination unit 320. As the inputs to the hot water supply classification device 300, the motion sensor 100 is connected to the behavior estimation unit 310, and the hot water supply amount sensor 200 is connected to the hot water destination determination unit 320. As the outputs from the hot water supply classification device 300, the plurality of first calculation devices 400 a to 400 c are connected to the hot water destination determination unit 320. The motion sensor 100 reacts to, for example, the existence of a person in the vicinity, and outputs the reaction count within a predetermined period. A plurality of motion sensors 100 are installed in different places so as to detect the living behaviors associated with the plurality of hot water destinations. In this embodiment, for example, assume that the motion sensors 100 are provided in the bathroom and the kitchen of the house.

The hot water supply amount sensor 200 measures the hot water usage.

The behavior estimation unit 310 of the hot water supply classification device 300 performs behavior estimation based on the installation place of the motion sensor 100 that has reacted. More specifically, if the reaction count of the motion sensor 100 corresponding to a hot water destination is larger than a threshold, the behavior estimation unit 310 estimates that the behavior corresponding to the hot water destination has occurred. Such behavior information associated with one of the plurality of hot water destinations is sent to the hot water destination determination unit 320 of the hot water supply classification device 300. The hot water destination determination unit 320 determines the hot water destination based on the behavior information obtained from the behavior estimation unit 310, obtains the hot water usage for each hot water destination from the measured hot water supply amount output from the hot water supply amount sensor 200, and sends it to one of the first calculation devices 400 a to 400 c in correspondence with the hot water destination.

As described above, the hot water supply classification device 300 is configured to determine the hot water destination corresponding to a person's behavior estimated based on the reaction of the motion sensor 100 that reacts to the existence of a person and classify the hot water usage measured by the hot water supply amount sensor 200 according to the hot water usage for each hot water destination.

As described above, the plurality of first calculation devices are provided in correspondence with the hot water destinations. The detailed arrangement will be described by exemplifying the first calculation device 400 a for bath. The arrangements and operations of the first calculation device 400 b for kitchen and the first calculation device 400 c for other hot water supply are the same as those of the first calculation device 400 a for bath except for the hot water destination.

The first calculation device 400 a for bath calculates a value representing the index of ordinary of the hot water usage for the bath (in other words, a index representing whether the hot water usage can be regarded as a usual amount of usage, that is, ordinary index) using a standard hot water supply model. If this value is smaller than a threshold, the hot water supply is determined to be of low ordinary. If this value is equal to or larger than the threshold, the hot water supply is determined to be of high ordinary.

Additional boiling-up is performed for hot water supply of low ordinary. To do this, an additional boiling-up amount calculation unit 510 of the second calculation device 500 calculates, for hot water supply of low ordinary, a first boiling-up amount of additional boiling-up.

On the other hand, for hot water supply of high ordinary, no additional boiling-up is performed. Instead, boiling-up is done, for example, in the middle of the night. For this purpose, a midnight boiling-up amount calculation unit 520 of the second calculation device 500 calculates, as a midnight boiling-up amount, a second boiling-up amount based on the integrated value of hot water supply amounts of high ordinary within, for example, a predetermined period (for example, one day).

More specifically, the first calculation device 400 a for bath includes a calculation unit 410 that calculates the hot water supply ordinary index, a hot water supply amount database (DB) 420 that stores a hot water supply table representing the hot water usage of each hot water destination (bath, in this case), a creation unit 430 that creates, based on the hot water supply table in the learning period, a standard hot water supply model representing the ratio of the number of days the integrated hot water usage has reached a specific amount within a predetermined period, the average of reach times the specific amount has been reached, and the standard deviation of the reach times, a standard hot water supply model database 440 that stores the standard hot water supply model, and a threshold setting unit 460 that sets the threshold to determine the level (presence/absence) of the ordinary in accordance with the input from an input device 450.

The calculation unit 410 includes a storage unit 411 that stores the normal integrated hot water usage, a probability calculation unit 412 that calculates, as the ordinary index, the product of the ratio and a probability based on the cumulative distribution function at a specific time in the normal distribution of the average and the standard deviation represented by the standard hot water supply model, and a threshold determination unit 413 that determines hot water supply whose calculated ordinary index value is smaller than the threshold set by the threshold setting unit 460 as hot water supply of low ordinary, and hot water supply whose ordinary index value is equal to or larger than the threshold as hot water supply of high ordinary.

The additional boiling-up amount calculation unit 510 and the midnight boiling-up amount calculation unit 520 of the second calculation device 500 are connected to the boiling device 600. The boiling device 600 performs water boiling (boiling-up) in an additional boiling-up amount designated by the additional boiling-up amount calculation unit 510. The boiling device 600 also performs boiling-up in a midnight boiling-up amount designated by the midnight boiling-up amount calculation unit 520. That is, boiling-up is performed in the middle of the night for hot water supply of high ordinary so as to cover the hot water supply of high ordinary on the next day.

In the system configuration of the hot water supply apparatus shown in FIG. 1, the hot water supply classification device 300, the first calculation devices 400 a to 400 c, and the second calculation device 500 can be implemented as a program to be executed by a computer 700. FIG. 2 illustrates the hardware configuration of the embodiment in this case. The computer 700 includes, for example, an input interface (IF) 710, a CPU 730, a memory 740, a hard disk 750, and an output interface (IF) 760, which are connected to a bus 720. The input device 450, the motion sensor 100, and the hot water supply amount sensor 200 shown in FIG. 1 are connected to the input interface (IF) 710 of the computer 700. The boiling device 600 shown in FIG. 1 is connected to the output interface (IF) 760. The hard disk 750 of the computer 700 is an example of a recording medium to store the program. The program is read out from the hard disk 750 to the memory 740 via the bus 720 and executed by the CPU 730. Note that the hot water supply classification device 300, the first calculation devices 400 a to 400 c, and the second calculation device 500 may be implemented as a plurality of programs to be executed by separate computers.

The detailed arrangements and operations of the hot water supply classification device 300, the first calculation device 400 a, and the second calculation device 500 will be described below.

FIG. 3 is a flowchart illustrating the detailed processing procedure of behavior estimation of the hot water supply classification device 300.

(Step S1) The behavior estimation unit 310 records, in the behavior recording table shown in FIG. 4, the reaction count of each of the motion sensors 100 in the bath and the kitchen during d min. The time interval d to measure the reaction count of each motion sensor 100 is set to, for example, 10 min.

(Step S2) Next, the behavior estimation unit 310 compares, for each time, the value of the reaction count of the motion sensor 100 for the bath and the value of the reaction count of the motion sensor 100 for the kitchen on the behavior recording table with a bath behavior threshold b_thr and a kitchen behavior threshold d_thr, respectively. If each reaction count exceeds the corresponding threshold, a bath behavior or a kitchen behavior is regarded to have been done during the d min, and 1 is recorded in the bath behavior or kitchen behavior of the behavior recording table. If the reaction count does not exceed the threshold, 0 is recorded. Note that the bath behavior threshold b_thr and the kitchen behavior threshold d_thr are set to, for example, 5 [times].

Steps S1 and S2 described above are repeated to estimate the person's behavior, and the estimated behavior is recorded for each time.

FIG. 5 is a flowchart illustrating the detailed processing procedure of hot water destination determination of the hot water supply classification device 300.

(Step S1) The hot water usage for each time is recorded in the hot water supply table shown in FIG. 6.

(Step S2) The behavior recording table is looked up for each time. If the bath behavior is 1 on the behavior recording table, the value of the hot water usage is entered to the field of bath hot water supply of the same time on the hot water supply table. If the kitchen behavior is 1, the hot water usage is entered to the field of kitchen hot water supply. Otherwise, the hot water usage is entered to the field of other hot water supply. For example, if both the bath behavior and the kitchen behavior are 1, the hot water usage is proportionally divided, and the resultant values are entered to the bath hot water supply and the kitchen hot water supply, respectively.

Repeating steps S1 and S2 described above allows to create the time-series data of the hot water usage for each hot water destination based on the measured values of bath and kitchen hot water supply amounts.

The time-series usage data is sent to the corresponding one of the first calculation device 400 a for bath, the first calculation device 400 b for kitchen, and the first calculation device 400 c for other hot water supply in accordance with the hot water destination.

The detailed processing procedure of the first calculation device 400 a will be described. The processing procedure is roughly divided into a learning phase for creating the standard hot water supply model, and a phase for calculating the ordinary index for a measured hot water usage. The learning phase is executed using the data of learning target days for bath hot water supply, kitchen hot water supply, and other hot water supply. The ordinary index calculation phase is executed for the data of ordinary index calculation target days. Note that when using a standard hot water supply model prepared in advance, the learning phase may be omitted, and the standard hot water supply model creation unit 430 may be omitted.

The learning phase is preferably repetitively executed periodically or at appropriate timings to update the created standard hot water supply model as needed.

The detailed processing procedure of the learning phase of the first calculation device 400 a will be described.

As shown in FIG. 6, the hot water usage for each time is described in the hot water supply amount DB 420. The standard hot water supply model creation unit 430 obtains, for the data of a plurality of learning target days, a ratio tr[s] of the number of days the integrated hot water usage of the learning target days has reached a specific amount “s” Litre and the reach time the specific amount has been reached, and calculates an average tm[s] and a standard deviation ts[s] of reach times.

The value of the specific amount s is set to, for example, a multiple of 10 equal to or larger than 0. The value s is increased until the ratio tr[s] of the number of days becomes 0. Let S be the set of values to be taken by s. The ratio tr[s] (sεS) of the number of days, the average tm[s] (sεS) of reach times, and the standard deviation ts[s] (sεS) are defined as the standard hot water supply model. This is stored in the standard hot water supply model DB 440.

FIG. 7 shows the data of learning target days to be used to create the standard hot water supply model. Assume that the standard hot water supply model is created using the data of three days, that is, DAY1, DAY2, and DAY3. DAY1 represents a pattern in which 10 L of hot water is used up to 12:00, and no hot water is used from then on. DAY2 represents a pattern in which 20 L of hot water is used up to 12:00, and no hot water is used from then on. DAY3 represents a pattern in which 20 L of hot water is used up to 24:00, and no hot water is used from then on.

Assume that the set S is {10,20}. Since the times the usage has reached 10 L are {12,6,12}, the average tm[10] of reach times is 10:00, and the standard deviation ts[10] is 3.46. Since 10 L of hot water is used on each day, the ratio tr[10] of the number of reach days is 1. Since the times of each day the usage has reached 20 L is {φ,12,24}, the average tm[20] of reach times is 18:00, and the standard deviation ts[20] is 8.48. Since the number of days the usage has reached 20 L is only two, the average tr[20] of the reach times is ⅔.

Before the description of the ordinary index calculation phase, threshold setting for determining ordinary will be explained.

The person who is the user can input the desired ordinary of energy saving using the input device 450. There are three ordinaries of energy saving, for example, “high”, “middle”, and “low”. The threshold setting unit 460 sets one of first, second, and third thresholds as a threshold to be used to determine ordinary in accordance with the input ordinary of energy saving. The first to third thresholds hold a relationship first threshold<second threshold<third threshold.

The detailed processing procedure of the ordinary index calculation phase of the first calculation device 400 a will be described with reference to the flowchart of FIG. 8.

(Step S1) The calculation unit 410 initializes the normal integrated hot water supply amount stored in the storage unit 411 to 0. A variable t of the time is set to a starting time 0:00. The threshold to be used to determine the ordinary is set to p_thr. The hot water usage at the time t is set to m(t).

(Step S2) The calculation unit 410 substitutes the value of a variable n+m(t) into a variable n′. If neither tm[n′] nor ts[n′] exists in the standard hot water supply model, the time is set forward to integrate m(t) until n′ exceeds the value existing in the standard hot water supply model. The integrated value is stored in the normal integrated hot water supply amount storage unit 411.

(Step S3) The probability calculation unit 412 of the calculation unit 410 calculates a value p representing the ordinary index by

p=½(1+erf{(t−tm[n′])/{ts[n′]*sqrt(2)}})*tr[n′]

“½(1+erf{(t−tm[n′])/{ts[n′]*sqrt(2)}})” of the right-hand side of the above-described equation represents the cumulative distribution function at the time t when a normal distribution of the average tm[n′] and the standard deviation ts[n′] is given. The calculated value represents whether the reach time the integrated hot water supply amount has reached n′ at the time t is earlier or later than the average, and ranges from 0 to 1. When, for example, the reach time is the same as the average, the probability calculation unit 412 returns 0.5. When the reach time is earlier than the average by ts[n′], the probability calculation unit 412 returns 0.15. When the reach time is earlier than the average by 2*ts[n′], the probability calculation unit 412 returns 0.025.

The value of 0.025 means that assuming a standard hot water supply model with the average tm[n′] and the standard deviation ts[n′] of the reach times, the probability that the integrated hot water supply amount reaches n′ at a time before tm[n′]−2*ts[n′] is 2.5% or less. Such hot water supply can be regarded as hot water supply of low ordinary.

In the above equation, tr[n′] is the value based on the standard hot water supply model. The value p of ordinary index is obtained by multiplying the ratio tr[n′] of the number of days the hot water usage has reached n′ as a weight.

For example, if the hot water usage has reached n′ in only 20 days out of 30 days, a standard hot water supply model representing the average and standard deviation of reach times the hot water usage reaches n′ is generated for 20 days, and the probability calculated from the model is multiplied by 20/30.

(Step S4) If ordinary index p>=threshold p_thr, the threshold determination unit 413 of the calculation unit 410 substitutes the value of the variable n′ into the variable n.

(Step S5) The calculation unit 410 advances the time t by one (10 min, in this case).

(Step S6) If the time t does not exceed the final time 24:00, the calculation unit 410 returns to step S2. Otherwise, the processing ends.

With the above processing, the value of the ordinary index and the value of the level (presence/absence) of the ordinary can be added to the hot water usage for each hot water destination at each time. These values are inserted into the hot water supply table in the hot water supply amount DB 420, as shown in FIG. 9. In the hot water supply table, for a hot water usage whose ordinary index p is determined in step S4 to be equal to or larger than the threshold p_thr, the ordinary is set to 1. For a hot water usage whose ordinary index p is determined to be smaller than the threshold p_thr, the ordinary is set to 0. Hot water supply whose ordinary is 0, that is, hot water supply of low ordinary is the target of additional boiling-up. For use of such hot water supply of low ordinary, the hot water usage is sent to the additional boiling-up amount calculation unit 510 of the second calculation device 500. The additional boiling-up amount calculation unit 510 receives the data as an additional boiling-up amount and sends it to the boiling device 600. The boiling device 600 boils water in the additional boiling-up amount and stores the hot water in the tank (not shown) of the hot water supply apparatus.

The detailed processing procedure of the midnight boiling-up amount calculation unit 520 of the second calculation device 500 will be described with reference to the flowchart of FIG. 10.

The midnight boiling-up amount calculation unit 520 of the second calculation device 500 acquires the hot water usage history for, for example, 30 days from the hot water supply amount DB 420, and calculates the midnight boiling-up amount using the history.

(Step S1) The midnight boiling-up amount calculation unit 520 acquires the final value of the normal integrated hot water usage calculated upon ordinary index calculation for the midnight boiling-up amount calculation target day.

(Step S2) The midnight boiling-up amount calculation unit 520 calculates the average and standard deviation of the final values obtained in step S1, and obtains average+2*standard deviation as the midnight boiling-up amount. Note that to decrease the possibility of hot water running out, the coefficient of the standard deviation is made large.

FIG. 11 shows examples of a time-rate change of the hot water supply amount when the ordinary of hot water supply is determined according to this embodiment. In FIG. 11, (a) shows the time-rate change of the amount [lit; liter] of hot water supply of high ordinary of a day, and (b) shows the time-rate change of the amount of hot water supply of low ordinary of the same day. In this day, use of hot water supply of low ordinary continues from about 11:00 to 16:00, and additional boiling-up is performed as much as this hot water supply according to this embodiment.

FIG. 12 shows an example of comparison between a case in which the water is boiled to fill up the tank (without control) using actual house data and a case in which the present embodiment is applied (with cooperative control). About 4.4 [KWh] of energy a day on average is saved, although the effects are reversed on three days.

According to the above-described embodiment, it is possible to provide a hot water supply apparatus capable of saving energy by performing additional boiling-up for each hot water destination when unusual hot water supply has occurred, and for normal use, boiling water, for example, in the middle of the night so as to decrease the total water boiling amount.

While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions. 

1. A hot water supply apparatus comprising: a first calculation device that calculates a value representing an ordinary index for a hot water usage of each hot water destination, determines hot water supply whose value is less than a threshold as hot water supply of low ordinary, and determines hot water supply whose value is not less than the threshold as hot water supply of high ordinary; and a second calculation device that calculates a first boiling-up amount for the hot water supply determined as the hot water supply of low ordinary, and calculates a second boiling-up amount for the hot water supply determined as the hot water supply of high ordinary.
 2. The apparatus according to claim 1, further comprising: a plurality of motion sensors installed in different places to detect existence of a person; a hot water supply amount sensor that measures the hot water usage; and a classification device that determines a hot water destination corresponding to a behavior of a person estimated based on an installation place where the motion sensor has reacted, and classifies the hot water usage as a hot water usage of each hot water destination.
 3. The apparatus according to claim 1, further comprising a boiling device that performs boiling-up in the first boiling-up amount and the second boiling-up amount.
 4. The apparatus according to claim 1, wherein the first calculation device comprises: a storage unit that stores an integrated amount of the hot water usages for each hot water destination; a database that stores a standard hot water supply model representing a ratio of the number of days the integrated amount has reached a specific amount within a predetermined period, an average of reach times the specific amount has been reached, and a standard deviation of the reach times; and a probability calculation unit that calculates, as a value representing the ordinary index, a product of the ratio and a probability based on a cumulative distribution function at a specific time in a normal distribution of the average and the standard deviation. 